Data

Model

Normalization

None

Z-standard

Min-Max

MaxAbs (−1, 1)

Quantile Transform

Quantile Normalize

Categorical - Poisson Target

Poisson Regression

Type of Loss

MSE

MSE

MSE

MSE

MSE

MSE

Total Loss

1.753

1.748

1.753

1.753

1.753

1.753

Bias

1.682

1.673

1.682

1.682

1.682

1.682

Variance

0.071

0.074

0.071

0.071

0.071

0.071

Noise

0.000

0.000

0.000

0.000

0.000

0.000

Variance-Bias Ratio

0.042

0.044

0.042

0.042

0.042

0.042

Percent Change from Raw

~

99.698

100.000

100.000

100.000

100.000

Decision Tree

Total Loss

1.559

1.591

1.499

1.499

1.499

1.499

Bias

1.351

1.435

1.314

1.314

1.314

1.314

Variance

0.208

0.157

0.185

0.185

0.185

0.185

Noise

0.000

0.000

0.000

0.000

0.000

0.000

Variance-Bias Ratio

0.154

0.109

0.141

0.141

0.141

0.141

Percent Change from Raw

~

102.089

96.164

96.164

96.164

96.164

Random Forest

Total Loss

1.581

1.661

1.581

1.581

1.581

1.581

Bias

1.434

1.559

1.434

1.434

1.434

1.434